1. Field of the Invention
The present invention relates generally to systems and methods for acquiring three-dimensional images, and more particularly to systems and methods for acquiring three-dimensional images by stereo techniques.
2. Description of the Prior Art
The use of 3-D imaging systems plays an increasingly important role in applications such as computer graphics, medical imaging, and automated manufacturing and inspection. To acquire a 3-D image, it is necessary to determine the distance or range to points in a scene (a region to be imaged, typically containing one or more objects). While the specific requirements of 3-D imaging systems will depend in part on the application for which it is used, desirable characteristics and properties of a 3-D imaging system common to many applications include the ability to generate dense, highly accurate range maps, rapid image acquisition, robustness to variations of surface properties and illumination, and precise correlation of range with spectral information.
References in the art disclose disparate approaches to acquiring 3-D images within a scene. These approaches may be broadly categorized into two types: passive and active. Passive 3-D imaging techniques do not require the introduction of additional radiant energy into the imaged scene. A first group of passive techniques utilizes multiple cameras, each camera capturing an image of the scene from a unique viewpoint. The resultant images are analyzed by feature-based or area-based matching methods. The foregoing group of passive techniques has the disadvantage of producing inaccuracies and/or dropouts in the range map corresponding to areas of the scene where there is little texture or inadequate illumination. Another group of passive techniques involves imaging the scene from multiple focal lengths and identifying, for each point, the focal length producing the sharpest focus. The range to the point can then be calculated utilizing the monotonic relationship between range and focal length. This group of techniques (deemed “range-to-focus” techniques) suffers from the aforementioned problem of dropouts/low accuracy in the range map associated with areas of little texture or inadequate illumination; furthermore, range-to-focus techniques are slow due to the number of images that must be captured.
Active 3-D imaging techniques are based on the introduction of additional radiant energy into the imaged scene. Active 3-D imaging techniques may be organized into three groups: time-of-flight, single-camera, and multiple-camera. Time-of-flight techniques measure (typically by direct timing or phase shift) the time required for light to travel from a source to a point in the scene and thereafter to a detector. These techniques require long acquisition times (because they require scanning of the light source over objects in the scene), utilize expensive equipment, and exhibit difficulty in correlating measured range with spectral data. Single-camera techniques involve the projection of structured light onto points in a scene imaged by the single camera. The source of the projected light provides one of the positions used for calculating range by triangulation, and the structure of the light identifies the particular projection point. Examples of such techniques include those described in U.S. Pat. No. 5,838,428 to Pipitone et al., System and Method for. High Resolution Range Imaging with Split Light Source and Pattern Mask, and in U.S. Pat. No. 4,648,717 to Ross et al., Method of Three-Dimensional Measurement with Few Projected Patterns. The projected light may take one of three forms: a single dot or plane sequentially scanned over the scene; a grid of lines, or; a spatially coded pattern. While the single camera techniques may produce useful results in applications where background lighting can be carefully controlled, they suffer from lack of robustness (resulting in dropouts or regions of low accuracy) in the absence of controlled background lighting.
Active multiple-camera techniques are similar to the passive multiple-camera techniques outlined above, with the addition of a projected structured light pattern onto the scene to assist in matching corresponding pixels in the plural images. A commonly used active multiple-camera technique (described, for example in Morano et al., Structured Light Using Pseudorandom Codes) uses projection of randomly generated light patterns. A problem with the use of random patterns is that large match windows (the use of which tends to miss or distort details of imaged surfaces) are required to ensure that accurate correspondences are computed. Further, the randomized nature of the light pattern means that its properties cannot be guaranteed, leading to matching failures and consequent dropouts.
Another group of active multi-camera techniques employs light patterns having spatially varying wavelengths. In accordance with these techniques, the light incident on a point within a scene has a spectral composition different from its neighboring points, which assists in identifying corresponding points in the plural images. Examples of techniques of this general description include those described in U.S. Pat. No. 5,621,529 to Gordon et al., Apparatus and Method for Projecting Laser Pattern with Reduced Speckle Noise, and in U.S. Pat. No. 6,493,095 to Song et al., Optional 3D Digitizer, System and Method for Digitizing an Object. However, the degree of assistance to the matching process provided by projection of this type of light pattern is limited due to the similarity of the light projected on adjacent pixels. In addition, regions having rapid variation in illumination or surface albedo create additional ambiguity in the matching process. Taken together, these limitations work to create regions in which the matching fails, resulting in dropouts.
In view of the foregoing discussion, there is a need for a 3-D image acquisition system that that overcomes the problems or deficiencies associated with existing techniques.